痉挛
物理医学与康复
肌肉张力
冲程(发动机)
轻瘫
改良阿什沃思量表
医学
物理疗法
上运动神经元
生活质量(医疗保健)
挛缩
疾病
肌萎缩侧索硬化
精神科
内科学
外科
护理部
工程类
机械工程
作者
Jörg Wissel,Aubrey Manack,Michael Brainin
出处
期刊:Neurology
[Lippincott Williams & Wilkins]
日期:2013-01-14
卷期号:80 (3_supplement_2)
被引量:299
标识
DOI:10.1212/wnl.0b013e3182762448
摘要
ABSTRACT
Poststroke spasticity (PSS)-related disability is emerging as a significant health issue for stroke survivors. There is a need for predictors and early identification of PSS in order to minimize complications and maladaptation from spasticity. Reviewing the literature on stroke and upper motor neuron syndrome, spasticity, contracture, and increased muscle tone measured with the Modified Ashworth Scale and the Tone Assessment Scale provided data on the dynamic time course of PSS. Prevalence estimates of PSS were highly variable, ranging from 4% to 42.6%, with the prevalence of disabling spasticity ranging from 2% to 13%. Data on phases of the PSS continuum revealed evidence of PSS in 4% to 27% of those in the early time course (1–4 weeks poststroke), 19% to 26.7% of those in the postacute phase (1–3 months poststroke), and 17% to 42.6% of those in the chronic phase (>3 months poststroke). Data also identified key risk factors associated with the development of spasticity, including lower Barthel Index scores, severe degree of paresis, stroke-related pain, and sensory deficits. Although such indices could be regarded as predictors of PSS and thus enable early identification and treatment, the different measures of PSS used in those studies limit the strength of the findings. To optimize evaluation in the different phases of care, the best possible assessment of PSS would make use of a combination of indicators for clinical impairment, motor performance, activity level, quality of life, and patient-reported outcome measures. Applying these recommended measures, as well as increasing our knowledge of the physiologic predictors of PSS, will enable us to perform clinical and epidemiologic studies that will facilitate identification and early, multimodal treatment.
科研通智能强力驱动
Strongly Powered by AbleSci AI